Parker Barnes

Aside

Skills

  • Specialized in R and the tidyverse

  • Machine learning with tidymodels

  • Databases: PostgreSQL/Redshift, T-SQL, dbplyr

  • Visualization: ggplot2, Shiny, Power BI

  • Analytics Pipeline Development with targets

  • MLOps with Github, Docker, AWS

  • Other Skills: R package development, Python (pandas, scikit-learn), Power BI, Excel

Disclaimer

This resume was made with pagedown.

Last updated on 2022-09-18.

Main

Parker Barnes

Education

University of Utah, Eccles School of Business

Master of Science, Business Analytics

Salt Lake City, UT

2021

3.95 GPA. Academic Scholarship, Lean Six Sigma Green Belt Certification

Capstone Project: ML tool predicting customer conversion in booking professional movers. Embedded in a custom R Shiny application

Brigham Young University

BS, Statistics, emphasis in Data Science.

Provo, UT

2017

Double Minor in CS & Math. 3.8 GPA. Academic Scholarship

Professional Experience

Data Scientist

Nursa™️

Murray, UT

Present - May, 2022

  • Built a data pipeline that clusters facilities into networks based on clinician labor patterns. Trains random forest model to predict job request rates and assigns price adjustments accordingly.
  • Developed internal R package that interfaces with company’s databases.
  • Automated monthly Stripe finance statements in RMarkdown and built friendly UI in R Shiny. Deployed using Docker and AWS

Data Scientist

PILYTIX

Austin, TX

May, 2022 - Dec, 2022

  • Remodeled a client’s A.I. pipeline by revamping SQL scripts to more accurately capture useful variables.
  • Explored and visualized variables to assess their predictability.
  • Trained and evaluated bayesian hierarchical models on selected variables to effectively predict “wins” and “losses” among sales opportunities
  • Contributed to internal R packages and analysis framework to facilitate more efficient and standardized analyses across clients

Data Analyst

International Academies of Emergency Dispatch (IAED)

Salt Lake City, UT

Dec, 2022 - May, 2021

  • Processed data requests for various stakeholders in the company by querying databases and visualizing in Power BI
  • Re-engineered automated data pipelines for company public-facing dashboards. Reduced memory usage and computation by 90% by applying STAR Schema principles.
  • Automated agency data monitoring process using a combination of SQL, R, and 2 project management APIs